Master the algorithms and techniques behind Data Science and AI to optimise your work. We are moving into the Fourth Industrial Revolution, and one of the most defining aspects of it is the way organisations are using data to completely revamp their business models, strategies and operations. As with all industrial revolutions, they leave no sectors unturned; the public service is no exception. There is a great deal of hype around what AI can do, and uncertainty around where it can be applied effectively. In this ePrimer series, we take a step back to explore what all these really means to a public officer operating in this new digital era by reducing the technical jargons into layman understanding.
For this first module, Data is a Team Sport, follow a visual book narrative style to explore what some applications of Data Science and AI are across the various domains and fields. The module will inspire you to take a hard look at your current state of work and think about whether there are avenues for you to apply new ways of doing your work better.
In this second module, Data Data Data, let us explore what is good data, what is Big Data, why data cleaning and preparation are important to the analytics workflow and many other interesting facts about data. You’ll never look at data the same way again!
In this third module, Once Upon A Chart, we first take a trip down memory lane to see why good visuals is not a modern invention and why they are essentials to good data storytelling. We’ll look at modern visual analytics principles we can all use to enhance our charts and dashboards.Numbers can’t speak for themselves, and you have the responsibility to bring them to life through good charts and visuals.
In the fourth module, I Learn, Therefore I am, we will explore the machine learning algorithms that have elevated Data Science and AI work to greater heights in the recent decade. We will gain an intuitive understanding of various machines learning algorithms, demystify what models are, and gain better appreciation of how to use them to better extract value from your data.
In this fifth module, I Came, I Saw, I Divide-And-Conquered, we see why jumping straight to tackle Data Science and AI projects without first sharpening the problem statement is a recipe for disaster. We go through a guide on how to scope a Data Science project, sharpening the problem statements, formulating lines of inquiries, and looking out for other key considerations so you start off on the right footing. Like they say, knowing is half the battle won. But scoping a project well, is knowing which battles you actually need to fight.
Note that the process for accessing CSC LEARN modules is generic
Connect with us on
